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Digital Image Processing 0909.452.01/0909.552.01 Fall 2003

Digital Image Processing 0909.452.01/0909.552.01 Fall 2003. Lecture 4 September 29, 2003. Shreekanth Mandayam ECE Department Rowan University http://engineering.rowan.edu/~shreek/fall03/dip/. Low-pass High-pass. Plan. Image Enhancement Detection of Discontinuities

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Digital Image Processing 0909.452.01/0909.552.01 Fall 2003

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  1. Digital Image Processing0909.452.01/0909.552.01Fall 2003 Lecture 4September 29, 2003 Shreekanth Mandayam ECE Department Rowan University http://engineering.rowan.edu/~shreek/fall03/dip/

  2. Low-pass High-pass Plan • Image Enhancement • Detection of Discontinuities • Edge detection (Sobel, Prewitt and Laplacian masks) • Image Spectrum • 2-D Fourier Transform (DFT & FFT) • Spectral Filtering • Lab 2: Spatial and Spectral Filtering

  3. DIP: Details

  4. Image Preprocessing Restoration Enhancement • Inverse filtering • Wiener filtering Spectral Domain Spatial Domain • Filtering • >>fft2/ifft2 • >>fftshift • Point Processing • >>imadjust • >>histeq • Spatial filtering • >>filter2

  5. z1 w1 w2 z2 w3 z3 w5 z5 w6 z6 z4 w4 w8 z8 z9 w9 w7 z7 Spatial Filtering (Masking) Portion of a digital image Mask Replace with R = w1z1 + w2z2 + ….. +w9z9

  6. -1 -1 -2 0 -1 1 0 0 0 2 -2 0 0 2 1 1 -1 1 Edge Detection Sobel Masks >>edgedemo >>edge • demos/demo2spatial_filtering/edgegradientdemo.m

  7. Continuous Fourier Transform (CFT) Frequency, [Hz] Phase Spectrum Amplitude Spectrum Inverse Fourier Transform (IFT) Recall: 1-D CFT

  8. Equal time intervals Recall: 1-D DFT • Discrete Domains • Discrete Time: k = 0, 1, 2, 3, …………, N-1 • Discrete Frequency: n = 0, 1, 2, 3, …………, N-1 • Discrete Fourier Transform • Inverse DFT Equal frequency intervals n = 0, 1, 2,….., N-1 k = 0, 1, 2,….., N-1

  9. n=0 1 2 3 4 n=N f=0 f = fs How to get the frequency axis in the DFT • The DFT operation just converts one set of number, x[k] into another set of numbers X[n] - there is no explicit definition of time or frequency • How can we relate the DFT to the CFT and obtain spectral amplitudes for discrete frequencies? (N-point FFT) Need to know fs

  10. n=0 N/2 n=N f=0 fs/2 f = fs DFT Properties • DFT is periodic X[n] = X[n+N] = X[n+2N] = ……… • I-DFT is also periodic! x[k] = x[k+N] = x[k+2N] = ………. • Where are the “low” and “high” frequencies on the DFT spectrum?

  11. 1-D FFT Demo http://engineering.rowan.edu/~shreek/spring03/ecomms/demos/dft.m >>fft

  12. u x v y 2-D Continuous Fourier Transform Spatial Frequency Domain Spatial Domain

  13. u=0 u=N/2 u=N v=N v=N/2 v=0 2-D Discrete Fourier Transform >>fft2 >>ifft2

  14. 2-D DFT Properties • Conjugate symmetry demos/demo3dft_properties/con_symm_and_trans.m • Rotation demos/demo3dft_properties/rotation.m • Separability demos/demo3dft_properties/separability.m >>fftshift

  15. Spectral Filtering: Radially Symmetric Filter u=-N/2 u=0 u=N/2 • Low-pass Filter demos/demo4freq_filtering/lowpass.m D(u,v) D0 v=N/2 v=0 v=-N/2

  16. Lab 2: Spatial & Spectral Filtering http://engineering.rowan.edu/~shreek/fall03/dip/lab2.html

  17. Summary

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